Decisions. Decisions. Decisions. Each of us is faced with making decisions each and everyday as part of our family lives and our business lives. As is well known in the art, decisions have become more complicated in that even simple business decisions are influenced by a myriad of factors. As is also well known, the numerous factors that contribute to any single decision are themselves more and more complicated in that they often times do not contribute equally to the decision, i.e., some factors weigh more heavily in a decision than do others. As the number of factors involved in making any one decision has grown, and the resultant importance in achieving the `correct` decision based on an analytical approach increases, it is well known that decision makers have turned to computers to aid them in the decision making process.
As is well known, computers provide a faster and more accurate vehicle to aid in the decision making process. As is also well known in this art, objective decision making is often based on numeric data used to describe various factors, or dimensions, of possible decision choices.
In one exemplary computer approach, factors affecting a decision are weighted and entered into a computer. The computer sums the weighted factors arithmetically, and the result of the simple addition is displayed on an output device such as a printer or display unit. But as it is well known in this art, complex decisions involve numerous factors, each of the factors involving numerous sub-factors, each of the sub-factors involving sub-sub-factors, and on and on. Thus, the simple method of weighting factors and summing their numeric equivalent is inappropriate, as it does not map to the complexity of decisions.
In another approach, a "spreadsheet" computer program is used to organize numeric data and generate results on a display device or printer device based on calculations performed on input data. In this approach, the results are often displayed in the form of "pie" charts and bar graphs. With this approach it is difficult to convey descriptive data since it would involve multiple dimensions of input data.
As is also well known, quantitative analytic techniques are being also used for what has been referred to as "benchmarking" product functionality and customer requirements. Benchmarking is a way of doing business that forces an external view to ensure correctness of objective goal setting. Benchmarking is an object-oriented process, a positive pro-active process to change operations in a structured manner to achieve superior performance. Benchmarking is a process to determine the best-in-class practices and metrics, an on-going process, a discovery and learning experience, with the desired state being that of becoming "best-in-class."
In addition to the previous approaches mentioned above, another approach has been to use vectors and their corresponding lengths, directions, and widths, to measure quantitatively a number of factors used in benchmarking. With this approach, only a bias force of less than one and only a ratio of original score to weighted score is utilized.
What is needed is a simple yet more formal mathematical method of using vectors and their inherent mathematical properties to support an improved comparative visual assessment methodology.